# Computer Project BUS ADM 210, Fall 2015

Computer Project

BUS ADM 210, Fall 2015

DUE: MONDAY, DECEMBER 7 BY 11:59 P.M. TO THE D2L DROPBOX

Instructions:

1. Follow the directions for each problem.

2. Use JMP for all calculations. Answer the questions thoroughly by showing your JMP outputs. If your JMP

outputs are not submitted then you will not receive full credit on the problem.

3. You will upload ONE file to the D2L Dropbox. It will consist of a Word/PDF/other file format document

containing all of your work and JMP outputs. This is the only file that should be uploaded to D2L. While your

JMP file used in Problems 1 & 2 does not need to be uploaded, your instructor/TA reserves the right to ask you

for this file to verify your work.

4. In your Word/PDF/document organize your responses by clearly numbering the problems and sub-parts in order.

5. It is okay to work with other students. However, each student’s project submission must be a product of his or

her own solutions to the problems. Any projects that are the same will NOT BE GRADED.

6. Please do not hesitate to contact your instructor or TA if you have any questions about the project. Questions

should be asked in a timely manner, not at the last minute!

7. This project is out of 50 possible points, with 2 bonus points built into Problem 4.

There are 3 data sets you will use with regard to this project:

1. On Problems 1 and 2, you will create your own data set of 45 gas station prices (regular, unleaded gasoline).

2. On Problems 3 and 4, please use the data file HousesProject.jmp, which consists of a random sample of 24

houses for sale in the area around UWM. Variables are: list price of the home (the column called “Price”), the

number of bedrooms (the column called “Beds”), and square feet (the column called “SquareFeet”).

3. On Problem 5, please use the data file Titanic.jmp. In this data file is a two-way table that compares economic

status to whether or not the passengers survived the sinking of the Titanic.

Problem 1: (11 points) We are going to explore the price of regular, unleaded gasoline in the Milwaukee area.

a)

What is the population of interest?

b) Find the gas prices of regular, unleaded gasoline at 45 gas stations in the Milwaukee area. You can do this using the

suggested websites below or you can drive around and record prices. Note that these websites typically report results in

terms of cheapest gas prices first. Please take this into consideration when generating your sample of 45 gas stations, which

should theoretically be a random sample.

AAA: http://aaa.opisnet.com/index.aspx (Click on the “Automotive” tab along the top. Then along the left hand side click on

“Fuel Prices”. On the next screen click on “Launch Finder” under the heading “Fuel Price Finder”)

milwaukeegasprices.com or gasbuddy.com

In your Word/PDF/document please indicate the source of your gasoline prices (website used, did you drive around, how

did you randomly select 45, etc.).

There is no need to upload your JMP file to D2L. However, your instructor/TA reserves the right to request you to provide

this file, so please keep it saved.

c)

In JMP, construct a histogram of the regular unleaded prices of gasoline. Describe the distribution by giving its shape,

center, and spread according to the histogram.

d) Have JMP produce the following summary statistics:

i.

Mean

ii.

Standard deviation

iii.

Median

iv.

The first quartile, Q 1

v.

The third quartile,

Q3

Problem 2: (17 points). We are interested in estimating the mean price of unleaded gasoline in the Milwaukee area. Please answer

the following questions:

a)

Using the data from Problem 1, have JMP determine the 99% confidence interval for the mean gasoline prices. Report your

answer as an interval of prices rounded to two decimal places.

b) Give an interpretation of this confidence interval.

c)

AAA lists out that the average price of gasoline in the Milwaukee area last month was $2.51. According to your data, can we

say there is a significant difference in the mean gasoline prices compared to last month?

i.

State the null and alternative hypotheses.

ii.

Describe the assumptions of this hypothesis test to determine if the test statistic you are using is appropriate. Fully

explain. Below are the four items you should comment on:

Does the Normality (or non-Normality) of your data set matter? Why or why not?

Is the population standard deviation, σ , known or unknown?

If σ is known, state what it is. If σ is unknown, state what we are using to estimate it.

Which distribution should we use to model probabilities related to the hypotheses?

iii.

Determine the p-value using JMP. Below are two suggested ways of doing this:

JMP’s Test Mean function

JMP’s Distribution Calculator: This can be found via Help Sample Data Teaching Scripts Interactive

Teaching Modules Distribution Calculator

iv.

Make a decision and state your conclusion to the hypothesis test in context of the original problem. Use a

significance level of α =0.01 (i.e. 1% significance level).

v.

Compare the results of your significance test to the 99% confidence interval for the mean gasoline price per gallon.

Does the conclusion in part (iv.) still hold for the confidence interval? Fully explain.

Part (c) of Problem 2 is used to test your Quantitative Literacy and will be graded on the following rubric:

Assessment Rubric (points)

Learning Outcome

Assessment Item

3

2

Students will

State the null and

Skillfully converts relevant

Completes conversion

recognize and

alternative

information into an appropriate

relevant information

construct

hypotheses to

and desired hypothesis,

into a hypothesis but

mathematical

determine if there are including using proper notation.

is only partially

models and/or

significant differences

appropriate or

hypotheses that

in the mean price of

accurate or uses

represent

gasoline.

improper notation.

quantitative

information.

Students will

evaluate the validity

of these models and

hypothesis.

1

Completes conversion

relevant information

into a hypothesis but is

inappropriate or

inaccurate.

Describe the

assumptions of this

hypothesis test to

determine if the test

statistic you are using

is appropriate.

Determine the pvalue of this

significance test using

JMP.

Accurately explains all 4 of the 4

bullet points listed above.

Accurately explains 3

of the 4 bullet points

listed above.

Accurately explains 1

or 2 of the 4 bullet

points listed above.

Analyses are attempted and all

are successful to answer the

problem. Analysis of the JMP

output is clearly and concisely

communicated.

Analyses are

attempted but are

incorrect in answering

the problem.

Students will reach

logical conclusions,

predictions, or

inferences.

Make a decision and

state your conclusion

to the hypothesis test

in context of the

original problem.

Rejection or failure to reject the

null hypothesis is correctly

communicated, including reason

for decision.

Provides correct conclusion in

proper context.

Students will assess

the reasonableness

of their conclusions.

Compare the results

of your significance

test to the 99%

confidence interval

for the mean gasoline

price per gallon.

Does the conclusion

in part (iv.) still hold

for the confidence

interval?

Uses the quantitative

information effectively as a basis

for deep and thoughtful

judgments in context. The

numerical results of the

confidence interval are explicitly

connected to the result of the

significance test. The

connection between the 99%

confidence interval and our

hypotheses at the 1%

significance level is properly

made.

Analyses are

attempted but are

only partially correct

in answering the

problem or analysis of

the JMP output is not

given.

Rejection or failure to

reject the null

hypothesis is correctly

communicated,

including reason for

decision.

Conclusion is not in

proper context or is

incorrectly stated.

Uses the quantitative

information correctly

but deeper

connections between

the confidence

interval and the

significance test are

not made.

Students will analyze

and manipulate

mathematical

models using

quantitative

information.

At attempt at a

decision and

conclusion is made but

both draw incorrect

conclusions on what

the information

means.

Uses the quantitative

information incorrectly

or does not provide

contextual basis for

the conclusion.

Connections between

the confidence interval

and the significance

test are not made.

Problem 3: (13 points) Using the JMP data set HousesProject.jmp, we want to determine if there is a significant difference in the

mean price of a 3-bedroom home compared to the mean price of a 4-bedroom home.

a) Give the summary statistics for the price of a 3-bedroom home versus a 4-bedroom home. The easiest way to generate this

is to go to Analyze Distribution and use “Price” in “Y, Columns” and Use “Beds” in the “By” window.

b) Create a side-by-side boxplot comparison between the price of 3-bedroom versus 4-bedroom homes. The easiest way to

generate this is to use Graph Builder. Go to Graph Graph Builder and drag “Price” into the Y area and “Beds” into the X

area. Then click on the boxplot icon along the top. Comment on the spread of the distributions and also on the medians of

the distributions.

c)

Is the mean house price for a 3-bedroom home significantly less than the mean house price for a 4-bedroom home?

i.

State the null and alternative hypotheses.

ii.

Use JMP to produce an output to test the difference in the means. Identify the appropriate p-value on the output.

iii.

Make a decision on the test at a significance level of α=0.02 .

iv.

State your conclusion to the question above in context.

d) Give the 95% confidence interval from the JMP output you used in part (c).

Problem 4: (4 points) Using the JMP data set HousesProject.jmp, we want to determine if the size of the house (SquareFeet) can

predict the list price (Price) of the home.

a)

Produce a scatterplot of Price (y axis) versus SquareFeet (x axis). Describe the form, direction, and strength of the

relationship between Price and SquareFeet. Note any potential outliers.

b) Using JMP, estimate the correlation coefficient between Price and SquareFeet.

c)

(Optional – worth 0.5 bonus points) Determine the simple linear regression line to predict Price using SquareFeet. In the

JMP output is the relationship significant at the 5% level? Justify your answer.

d) (Optional – worth 0.5 bonus points) What is the slope

respect to SquareFeet.

b1 ? Give the interpretation of what it means about the Price with

e) (Optional – worth 0.5 bonus points) Using the regression equation, predict the price of a 2000-square-foot home.

f)

(Optional – worth 0.5 bonus points) What percent of the variation in Price can be explained by this regression equation?

Problem 5: (5 points) In 1912 the British luxury passenger ship Titanic struck an iceberg and sank on its way to New York City. Think

of the Titanic disaster as an experiment in how the people of that time behaved when faced with death in a situation where only

some can escape, and consider the passengers from the data file Titanic.jmp as a sample from the population of their peers. We

want to determine if economic status and survival are independent.

Economic Status

Highest

Middle

Lowest

a)

Survival Status

Die

Survive

d

d

117

187

526

186

163

112

State the null and alternative hypotheses.

b) Produce a contingency table output in JMP. In this table, have JMP display the “Count,” “Expected,” and “Cell Chi Square”

values.

c)

Give the p-value and the decision from the test at the 5% significance level.

d) What do you conclude from this significance test at the 5% level? State your conclusion in the context of the problem.

BUS ADM 210, Fall 2015

DUE: MONDAY, DECEMBER 7 BY 11:59 P.M. TO THE D2L DROPBOX

Instructions:

1. Follow the directions for each problem.

2. Use JMP for all calculations. Answer the questions thoroughly by showing your JMP outputs. If your JMP

outputs are not submitted then you will not receive full credit on the problem.

3. You will upload ONE file to the D2L Dropbox. It will consist of a Word/PDF/other file format document

containing all of your work and JMP outputs. This is the only file that should be uploaded to D2L. While your

JMP file used in Problems 1 & 2 does not need to be uploaded, your instructor/TA reserves the right to ask you

for this file to verify your work.

4. In your Word/PDF/document organize your responses by clearly numbering the problems and sub-parts in order.

5. It is okay to work with other students. However, each student’s project submission must be a product of his or

her own solutions to the problems. Any projects that are the same will NOT BE GRADED.

6. Please do not hesitate to contact your instructor or TA if you have any questions about the project. Questions

should be asked in a timely manner, not at the last minute!

7. This project is out of 50 possible points, with 2 bonus points built into Problem 4.

There are 3 data sets you will use with regard to this project:

1. On Problems 1 and 2, you will create your own data set of 45 gas station prices (regular, unleaded gasoline).

2. On Problems 3 and 4, please use the data file HousesProject.jmp, which consists of a random sample of 24

houses for sale in the area around UWM. Variables are: list price of the home (the column called “Price”), the

number of bedrooms (the column called “Beds”), and square feet (the column called “SquareFeet”).

3. On Problem 5, please use the data file Titanic.jmp. In this data file is a two-way table that compares economic

status to whether or not the passengers survived the sinking of the Titanic.

Problem 1: (11 points) We are going to explore the price of regular, unleaded gasoline in the Milwaukee area.

a)

What is the population of interest?

b) Find the gas prices of regular, unleaded gasoline at 45 gas stations in the Milwaukee area. You can do this using the

suggested websites below or you can drive around and record prices. Note that these websites typically report results in

terms of cheapest gas prices first. Please take this into consideration when generating your sample of 45 gas stations, which

should theoretically be a random sample.

AAA: http://aaa.opisnet.com/index.aspx (Click on the “Automotive” tab along the top. Then along the left hand side click on

“Fuel Prices”. On the next screen click on “Launch Finder” under the heading “Fuel Price Finder”)

milwaukeegasprices.com or gasbuddy.com

In your Word/PDF/document please indicate the source of your gasoline prices (website used, did you drive around, how

did you randomly select 45, etc.).

There is no need to upload your JMP file to D2L. However, your instructor/TA reserves the right to request you to provide

this file, so please keep it saved.

c)

In JMP, construct a histogram of the regular unleaded prices of gasoline. Describe the distribution by giving its shape,

center, and spread according to the histogram.

d) Have JMP produce the following summary statistics:

i.

Mean

ii.

Standard deviation

iii.

Median

iv.

The first quartile, Q 1

v.

The third quartile,

Q3

Problem 2: (17 points). We are interested in estimating the mean price of unleaded gasoline in the Milwaukee area. Please answer

the following questions:

a)

Using the data from Problem 1, have JMP determine the 99% confidence interval for the mean gasoline prices. Report your

answer as an interval of prices rounded to two decimal places.

b) Give an interpretation of this confidence interval.

c)

AAA lists out that the average price of gasoline in the Milwaukee area last month was $2.51. According to your data, can we

say there is a significant difference in the mean gasoline prices compared to last month?

i.

State the null and alternative hypotheses.

ii.

Describe the assumptions of this hypothesis test to determine if the test statistic you are using is appropriate. Fully

explain. Below are the four items you should comment on:

Does the Normality (or non-Normality) of your data set matter? Why or why not?

Is the population standard deviation, σ , known or unknown?

If σ is known, state what it is. If σ is unknown, state what we are using to estimate it.

Which distribution should we use to model probabilities related to the hypotheses?

iii.

Determine the p-value using JMP. Below are two suggested ways of doing this:

JMP’s Test Mean function

JMP’s Distribution Calculator: This can be found via Help Sample Data Teaching Scripts Interactive

Teaching Modules Distribution Calculator

iv.

Make a decision and state your conclusion to the hypothesis test in context of the original problem. Use a

significance level of α =0.01 (i.e. 1% significance level).

v.

Compare the results of your significance test to the 99% confidence interval for the mean gasoline price per gallon.

Does the conclusion in part (iv.) still hold for the confidence interval? Fully explain.

Part (c) of Problem 2 is used to test your Quantitative Literacy and will be graded on the following rubric:

Assessment Rubric (points)

Learning Outcome

Assessment Item

3

2

Students will

State the null and

Skillfully converts relevant

Completes conversion

recognize and

alternative

information into an appropriate

relevant information

construct

hypotheses to

and desired hypothesis,

into a hypothesis but

mathematical

determine if there are including using proper notation.

is only partially

models and/or

significant differences

appropriate or

hypotheses that

in the mean price of

accurate or uses

represent

gasoline.

improper notation.

quantitative

information.

Students will

evaluate the validity

of these models and

hypothesis.

1

Completes conversion

relevant information

into a hypothesis but is

inappropriate or

inaccurate.

Describe the

assumptions of this

hypothesis test to

determine if the test

statistic you are using

is appropriate.

Determine the pvalue of this

significance test using

JMP.

Accurately explains all 4 of the 4

bullet points listed above.

Accurately explains 3

of the 4 bullet points

listed above.

Accurately explains 1

or 2 of the 4 bullet

points listed above.

Analyses are attempted and all

are successful to answer the

problem. Analysis of the JMP

output is clearly and concisely

communicated.

Analyses are

attempted but are

incorrect in answering

the problem.

Students will reach

logical conclusions,

predictions, or

inferences.

Make a decision and

state your conclusion

to the hypothesis test

in context of the

original problem.

Rejection or failure to reject the

null hypothesis is correctly

communicated, including reason

for decision.

Provides correct conclusion in

proper context.

Students will assess

the reasonableness

of their conclusions.

Compare the results

of your significance

test to the 99%

confidence interval

for the mean gasoline

price per gallon.

Does the conclusion

in part (iv.) still hold

for the confidence

interval?

Uses the quantitative

information effectively as a basis

for deep and thoughtful

judgments in context. The

numerical results of the

confidence interval are explicitly

connected to the result of the

significance test. The

connection between the 99%

confidence interval and our

hypotheses at the 1%

significance level is properly

made.

Analyses are

attempted but are

only partially correct

in answering the

problem or analysis of

the JMP output is not

given.

Rejection or failure to

reject the null

hypothesis is correctly

communicated,

including reason for

decision.

Conclusion is not in

proper context or is

incorrectly stated.

Uses the quantitative

information correctly

but deeper

connections between

the confidence

interval and the

significance test are

not made.

Students will analyze

and manipulate

mathematical

models using

quantitative

information.

At attempt at a

decision and

conclusion is made but

both draw incorrect

conclusions on what

the information

means.

Uses the quantitative

information incorrectly

or does not provide

contextual basis for

the conclusion.

Connections between

the confidence interval

and the significance

test are not made.

Problem 3: (13 points) Using the JMP data set HousesProject.jmp, we want to determine if there is a significant difference in the

mean price of a 3-bedroom home compared to the mean price of a 4-bedroom home.

a) Give the summary statistics for the price of a 3-bedroom home versus a 4-bedroom home. The easiest way to generate this

is to go to Analyze Distribution and use “Price” in “Y, Columns” and Use “Beds” in the “By” window.

b) Create a side-by-side boxplot comparison between the price of 3-bedroom versus 4-bedroom homes. The easiest way to

generate this is to use Graph Builder. Go to Graph Graph Builder and drag “Price” into the Y area and “Beds” into the X

area. Then click on the boxplot icon along the top. Comment on the spread of the distributions and also on the medians of

the distributions.

c)

Is the mean house price for a 3-bedroom home significantly less than the mean house price for a 4-bedroom home?

i.

State the null and alternative hypotheses.

ii.

Use JMP to produce an output to test the difference in the means. Identify the appropriate p-value on the output.

iii.

Make a decision on the test at a significance level of α=0.02 .

iv.

State your conclusion to the question above in context.

d) Give the 95% confidence interval from the JMP output you used in part (c).

Problem 4: (4 points) Using the JMP data set HousesProject.jmp, we want to determine if the size of the house (SquareFeet) can

predict the list price (Price) of the home.

a)

Produce a scatterplot of Price (y axis) versus SquareFeet (x axis). Describe the form, direction, and strength of the

relationship between Price and SquareFeet. Note any potential outliers.

b) Using JMP, estimate the correlation coefficient between Price and SquareFeet.

c)

(Optional – worth 0.5 bonus points) Determine the simple linear regression line to predict Price using SquareFeet. In the

JMP output is the relationship significant at the 5% level? Justify your answer.

d) (Optional – worth 0.5 bonus points) What is the slope

respect to SquareFeet.

b1 ? Give the interpretation of what it means about the Price with

e) (Optional – worth 0.5 bonus points) Using the regression equation, predict the price of a 2000-square-foot home.

f)

(Optional – worth 0.5 bonus points) What percent of the variation in Price can be explained by this regression equation?

Problem 5: (5 points) In 1912 the British luxury passenger ship Titanic struck an iceberg and sank on its way to New York City. Think

of the Titanic disaster as an experiment in how the people of that time behaved when faced with death in a situation where only

some can escape, and consider the passengers from the data file Titanic.jmp as a sample from the population of their peers. We

want to determine if economic status and survival are independent.

Economic Status

Highest

Middle

Lowest

a)

Survival Status

Die

Survive

d

d

117

187

526

186

163

112

State the null and alternative hypotheses.

b) Produce a contingency table output in JMP. In this table, have JMP display the “Count,” “Expected,” and “Cell Chi Square”

values.

c)

Give the p-value and the decision from the test at the 5% significance level.

d) What do you conclude from this significance test at the 5% level? State your conclusion in the context of the problem.

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